Evaluating the Persuasiveness of Mobile Health: The Intersection of Persuasive System Design and Data Science

Persuasive technology is an umbrella term that encompasses any software (e.g., mobile app) or hardware (e.g., smartwatch) designed to influence users to perform a preferable behavior once or on a long-term basis. Considering the ubiquitous nature of mobile devices across all socioeconomic groups, user behavior modification thrives under the personalized care that persuasive technology can offer. This research examines the roles psychological characteristics play in interpreted mHealth screen perceived persuasiveness. A review of the literature revealed a gap regarding how developers of digital health technologies are often tasked with developing tools designed to engage patients, yet little emphasis has been placed on understanding what psychological characteristics motivate and demotivate their users to engage with digital health technologies. Developers must move past using a cookie-cutter, one size fits all solution, and seek to develop digital health technologies designed to traverse the terrain that navigates between the fluid nature of goals and user preferences. This terrain is often determined by user’s psychological characteristics and demographic (control) variables. An experiment was designed to evaluate how psychological characteristics (self-efficacy, xiv health consciousness, health motivation, and the Big Five personality traits) impact the perceived persuasiveness of digital health technologies utilizing the Persuasive System Design (PSD) framework. This study used multiple linear regressions and Contrast, a publicly available Python implementation of the contrast pattern mining algorithm Search and Testing for Understandable Consistent Contrasts (STUCCO), to study the multifaceted needs of the users of digital health technologies based on psychological characteristics. The results of this experiment show psychological characteristics (selfefficacy, health consciousness, health motivation, and extraversion) enhancing the perceived persuasiveness of digital health technologies. The findings of the study revealed that screens utilizing techniques for the primary task support have high perceived persuasiveness scores. System credibility techniques were found to be a contributor to perceived persuasiveness and should be used in the development of persuasive technologies. The results of this study show practitioners should abstain from using social support techniques. Persuasive techniques from the social support category were found to have very low perceived persuasive scores which indicate a lower ability to persuade mHealth app users to utilize the tool. The findings strongly suggest the distribution of perceived persuasiveness shifts from negatively skewed to positively skewed as participants get older. Additionally, this shift occurs earlier in females (i.e., in the 40-59 age group) compared to males who do not shift until the oldest age group (i.e., in the 60 and older age group). The results imply that an individual user’s psychological characteristics affect interpreted mHealth screen perceived persuasiveness, and that combinations of persuasive principles and psychological characteristics lead to greater perceived persuasiveness

Medical Internet of Things: A Survey of the Current Threat and Vulnerability Landscape

The Internet of things (IoT) is a system that utilizes the Internet to facilitate communication between sensors and devices. Given the ubiquitous nature of IoT devices, it is seemingly inevitable that IoT would be used as a conduit to transform healthcare. One such medical IoT (mIoT) device that is revolutionizing healthcare is the medical implant device. These mIoT implant devices which control insulin pumps, cardioverter defibrillators and bone growth stimulators have redefined the way patient data is accessed, and healthcare is delivered. These implant devices are a double-edged sword. While they allow for the effective and efficient noninvasive treatment of patients, this external communication makes the medical implants vulnerable to cyberattacks synonymous with IoT devices. As a result, privacy and security vulnerabilities have surfaced as pronounced challenges for mIoT devices. This work summarizes and synthesizes the inherent vulnerabilities associated with mIoT devices and the implications regarding patient safety

The Intersection of Persuasive System Design and Personalization in Mobile Health: Statistical Evaluation

Background: Persuasive technology is an umbrella term that encompasses software (eg, mobile apps) or hardware (eg, smartwatches) designed to influence users to perform preferable behavior once or on a long-term basis. Considering the ubiquitous nature of mobile devices across all socioeconomic groups, user behavior modification thrives under the personalized care that persuasive technology can offer. However, there is no guidance for developing personalized persuasive technologies based on the psychological characteristics of users. Objective: This study examined the role that psychological characteristics play in interpreted mobile health (mHealth) screen perceived persuasiveness. In addition, this study aims to explore how users’ psychological characteristics drive the perceived persuasiveness of digital health technologies in an effort to assist developers and researchers of digital health technologies by creating more engaging solutions. Methods: An experiment was designed to evaluate how psychological characteristics (self-efficacy, health consciousness, health motivation, and the Big Five personality traits) affect the perceived persuasiveness of digital health technologies, using the persuasive system design framework. Participants (n=262) were recruited by Qualtrics International, Inc, using the web-based survey system of the XM Research Service. This experiment involved a survey-based design with a series of 25 mHealth app screens that featured the use of persuasive principles, with a focus on physical activity. Exploratory factor analysis and linear regression were used to evaluate the multifaceted needs of digital health users based on their psychological characteristics. Results: The results imply that an individual user’s psychological characteristics (self-efficacy, health consciousness, health motivation, and extraversion) affect interpreted mHealth screen perceived persuasiveness, and combinations of persuasive principles and psychological characteristics lead to greater perceived persuasiveness. The F test (ie, ANOVA) for model 1 was significant (F9,6540=191.806; PR2 of 0.208, indicating that the demographic variables explained 20.8% of the variance in perceived persuasiveness. Gender was a significant predictor, with women having higher perceived persuasiveness (P=.008) relative to men. Age was a significant predictor of perceived persuasiveness with individuals aged 40 to 59 years (PPF13,6536=341.035; PR2 of 0.403, indicating that the demographic variables self-efficacy, health consciousness, health motivation, and extraversion together explained 40.3% of the variance in perceived persuasiveness. Conclusions: This study evaluates the role that psychological characteristics play in interpreted mHealth screen perceived persuasiveness. Findings indicate that self-efficacy, health consciousness, health motivation, extraversion, gender, age, and education significantly influence the perceived persuasiveness of digital health technologies. Moreover, this study showed that varying combinations of psychological characteristics and demographic variables affected the perceived persuasiveness of the primary persuasive technology category

mHealth Cross-Contamination of User Health Data: Android Platform Analysis

Although a plethora of mobile health (mHealth) applications containing user data and patient generated health data (PGHD) exist, there appears to be a research gap addressing the user’s susceptibility of cross- contamination of data. The objective of this study is to seek a deeper understanding of the risk of cross- contamination of health data from the use of multiple mHealth applications, wearables, and other Internet of Things (IoT) devices. Through the review of recent publications addressing the prevalent information leaks in Android devices, the cross-talk between mobile applications, the vulnerability of mHealth applications, and user habits in regard to account creation this research study aims to explore the possibility that the user data, although held in silos, can be penetrated to create a compilation of the users\u27 comprehensive health information